Object detection networks.
The network SECOND-iou [1]}, [2]} is a two stage voxel-based 3D object detector which uses a PointNet [3]} backbone to extract voxel features from groupings of points and consists of a grouping layer, a region proposal network (RPN) and an ROI refinement head. It is a modified version of SECOND [1]} proposed in [2]}, with the extra refinement head. The region features for prototype computation are obtained at the output of the RPN head, and the classification loss at this stage is down-weighed during adaptation. PointRCNN is a two stage point-based network with a similar PointNet backbone for feature extraction that generates 3D region proposals through a bottom-up approach through foreground segmentation. This is followed by a refinement network. We implement adaptation for PointRCNN in this second stage.
